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dc.contributor.authorTang, Qing
dc.contributor.authorAbel, Marie-Hélène
hal.structure.identifierLaboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
dc.contributor.authorNegre, Elsa
dc.date.accessioned2022-02-22T15:47:31Z
dc.date.available2022-02-22T15:47:31Z
dc.date.issued2021
dc.identifier.urihttps://basepub.dauphine.psl.eu/handle/123456789/22719
dc.language.isoenen
dc.subjectonline collaborative learningen
dc.subjectlearner’s activityen
dc.subjectlearner’s mooden
dc.subjectlearner modelen
dc.subjectrecommender systemen
dc.subject.ddc004en
dc.titleImprove Learner-based Recommender System with Learner’s Mood in Online Learning Platformen
dc.typeCommunication / Conférence
dc.description.abstractenLearning with huge amount of online educational resources is challenging, especially when variety resources come from different online systems. Recommender systems are used to help learners obtain appropriate resources efficiently in online learning. To improve the performance of recommender system, more and more learner’s attributes (e.g. learning style, learning ability, knowledge level, etc.) have been considered. We are committed to proposing a learner-based recommender system, not just consider learner’s physical features, but also learner’s mood while learning. This recommender system can make recommendations according to the links between learners, and can change the recommendation strategy as learner’s mood changes, which will have a certain improvement in recommendation accuracy and makes recommended results more reasonable and interpretable.en
dc.identifier.citationpages1704-1709en
dc.relation.ispartoftitle20th IEEE International Conference on Machine Learning and Applications (ICMLA 2021)en
dc.relation.ispartofpublnameIEEE - Institute of Electrical and Electronics Engineersen
dc.relation.ispartofpublcityPiscataway, NJen
dc.subject.ddclabelInformatique généraleen
dc.relation.ispartofisbn978-1-6654-4337-1en
dc.relation.conftitle20th IEEE International Conference on Machine Learning and Applications (ICMLA 2021)en
dc.relation.confdate2021-12
dc.relation.confcityPasadena, CAen
dc.relation.confcountryUnited Statesen
dc.relation.forthcomingnonen
dc.identifier.doi10.1109/ICMLA52953.2021.00271en
dc.description.ssrncandidatenon
dc.description.halcandidatenonen
dc.description.readershiprechercheen
dc.description.audienceInternationalen
dc.relation.Isversionofjnlpeerreviewednonen
dc.date.updated2022-02-22T15:42:45Z
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